WO2023279533A1 - 一种储充站仿真建模方法及终端 - Google Patents
一种储充站仿真建模方法及终端 Download PDFInfo
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- WO2023279533A1 WO2023279533A1 PCT/CN2021/118996 CN2021118996W WO2023279533A1 WO 2023279533 A1 WO2023279533 A1 WO 2023279533A1 CN 2021118996 W CN2021118996 W CN 2021118996W WO 2023279533 A1 WO2023279533 A1 WO 2023279533A1
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- Prior art keywords
- converter
- storage battery
- energy storage
- output
- energy management
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- 238000005094 computer simulation Methods 0.000 title claims abstract description 28
- 238000000034 method Methods 0.000 title claims abstract description 21
- 238000004146 energy storage Methods 0.000 claims abstract description 128
- 238000004088 simulation Methods 0.000 claims abstract description 59
- 238000004590 computer program Methods 0.000 claims description 9
- 238000004364 calculation method Methods 0.000 abstract description 9
- 230000009286 beneficial effect Effects 0.000 description 4
- HEZMWWAKWCSUCB-PHDIDXHHSA-N (3R,4R)-3,4-dihydroxycyclohexa-1,5-diene-1-carboxylic acid Chemical compound O[C@@H]1C=CC(C(O)=O)=C[C@H]1O HEZMWWAKWCSUCB-PHDIDXHHSA-N 0.000 description 3
- 238000006243 chemical reaction Methods 0.000 description 2
- 238000007599 discharging Methods 0.000 description 2
- 230000005611 electricity Effects 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 230000008859 change Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
- 238000000844 transformation Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/28—Arrangements for balancing of the load in a network by storage of energy
- H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
- H02J3/322—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means the battery being on-board an electric or hybrid vehicle, e.g. vehicle to grid arrangements [V2G], power aggregation, use of the battery for network load balancing, coordinated or cooperative battery charging
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2310/00—The network for supplying or distributing electric power characterised by its spatial reach or by the load
- H02J2310/40—The network being an on-board power network, i.e. within a vehicle
- H02J2310/48—The network being an on-board power network, i.e. within a vehicle for electric vehicles [EV] or hybrid vehicles [HEV]
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E70/00—Other energy conversion or management systems reducing GHG emissions
- Y02E70/30—Systems combining energy storage with energy generation of non-fossil origin
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/60—Other road transportation technologies with climate change mitigation effect
- Y02T10/70—Energy storage systems for electromobility, e.g. batteries
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/60—Other road transportation technologies with climate change mitigation effect
- Y02T10/7072—Electromobility specific charging systems or methods for batteries, ultracapacitors, supercapacitors or double-layer capacitors
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02T90/10—Technologies relating to charging of electric vehicles
- Y02T90/12—Electric charging stations
Definitions
- the invention relates to the field of new energy technologies, in particular to a simulation modeling method and terminal for a storage and charging station.
- the energy storage charging station contains a group of energy storage batteries, which can store a part of the electric energy in the energy storage battery in advance when the charging station is free, and then release it when the electric vehicle has a useful power demand, thereby improving the efficiency of the charging station.
- the technical problem to be solved by the present invention is: to provide a storage and charging station simulation modeling method and terminal, which can predict the operation result of the energy management strategy.
- a simulation modeling method for a storage and charging station comprising the steps of:
- a storage and charging station simulation modeling terminal including a memory, a processor, and a computer program stored on the memory and operable on the processor, and the processor implements the following steps when executing the computer program:
- the beneficial effects of the present invention are: after setting the parameter values and constraint conditions of the energy management strategy, calculate the output amount of the energy storage battery and the converter according to the parameter value of the energy management strategy, and calculate the state of charge of the energy storage battery according to the calculation result and the power consumption of the converter; judge whether the output of the converter and the energy storage battery, the state of charge of the energy storage battery, and the power consumption of the converter meet the constraints of the energy management strategy, and if so, implement If there is no device alarm during the energy management strategy, record the simulation result corresponding to the energy management strategy; therefore, perform simulation calculation on the set energy management strategy, and judge whether the energy management strategy meets the execution conditions according to the simulation data, so as to automatically predict the energy management The result of running the strategy.
- Fig. 1 is a flow chart of a simulation modeling method for a storage and charging station according to an embodiment of the present invention
- Fig. 2 is a schematic diagram of a simulation modeling terminal of a storage and charging station according to an embodiment of the present invention
- Fig. 3 is a flow chart of specific steps of a simulation modeling method for a storage and charging station according to an embodiment of the present invention.
- an embodiment of the present invention provides a simulation modeling method for a storage and charging station, including steps:
- the beneficial effects of the present invention are: after setting the parameter values and constraints of the energy management strategy, calculate the output of the energy storage battery and the converter according to the parameter values of the energy management strategy, and calculate the energy storage according to the calculation results
- the state of charge of the battery and the power consumption of the converter determine whether the output of the converter and the energy storage battery, the state of charge of the energy storage battery, and the power consumption of the converter meet the constraints of the energy management strategy , if it is met and there is no device alarm during the execution of the energy management strategy, record the simulation result corresponding to the energy management strategy; therefore, perform simulation calculation on the set energy management strategy, and judge whether the energy management strategy meets the execution conditions according to the simulation data, In this way, the operation result of the energy management strategy can be predicted automatically.
- calculating the output of the converter and the energy storage battery includes:
- the total power demand of multiple charging piles can be calculated, so that the variable current can be calculated in combination with the parameter values of the energy management strategy and the total power demand. Therefore, combined with the request information of the charging pile, the output amount can be calculated more accurately.
- calculating the state of charge of the energy storage battery and the power consumption of the converter respectively includes:
- V i , SOC i F ess (SOC i-1 , V i-1 , W e );
- W e represents the output amount of the energy storage battery, and i represents the time period
- W pa , P pa F PCS (W p , ⁇ t);
- Wp represents the power output of the converter
- ⁇ t represents the difference between the request start time and the request end time of the current and voltage request.
- the energy storage battery SOC and the DC bus voltage are updated through the energy storage battery model and the output rating of the energy storage battery, and the AC power consumption and output power are calculated through the converter model and the output rating of the converter. Therefore The state of charge of the energy storage battery and the power consumption of the converter can be accurately calculated through the simulation model, so as to obtain the simulation results of the energy management strategy.
- ⁇ t represents the difference between the request start time and the request end time of the current and voltage request.
- the auxiliary source power consumption is calculated by calling the auxiliary source model of the energy management system, so as to obtain the simulation result of the energy management strategy.
- FIG. 2 another embodiment of the present invention provides a simulation modeling terminal of a storage and charging station, including a memory, a processor, and a computer program stored in the memory and operable on the processor, the processor The following steps are implemented when the computer program is executed:
- the beneficial effects of the present invention are: after setting the parameter values and constraint conditions of the energy management strategy, calculate the output amount of the energy storage battery and the converter according to the parameter values of the energy management strategy, and calculate the energy storage capacity based on the calculation results.
- the state of charge of the battery and the power consumption of the converter determine whether the output of the converter and the energy storage battery, the state of charge of the energy storage battery, and the power consumption of the converter meet the constraints of the energy management strategy , if it is met and there is no device alarm during the execution of the energy management strategy, record the simulation result corresponding to the energy management strategy; therefore, perform simulation calculation on the set energy management strategy, and judge whether the energy management strategy meets the execution conditions according to the simulation data, In this way, the operation result of the energy management strategy can be predicted automatically.
- calculating the output of the converter and the energy storage battery includes:
- the total power demand of multiple charging piles can be calculated, so that the variable current can be calculated in combination with the parameter values of the energy management strategy and the total power demand. Therefore, combined with the request information of the charging pile, the output amount can be calculated more accurately.
- calculating the state of charge of the energy storage battery and the power consumption of the converter respectively includes:
- V i , SOC i F ess (SOC i-1 , V i-1 , W e );
- W e represents the output amount of the energy storage battery, and i represents the time period
- W pa , P pa F PCS (W p , ⁇ t);
- Wp represents the power output of the converter
- ⁇ t represents the difference between the request start time and the request end time of the current and voltage request.
- the energy storage battery SOC and the DC bus voltage are updated through the energy storage battery model and the output rating of the energy storage battery, and the AC power consumption and output power are calculated through the converter model and the output rating of the converter. Therefore The state of charge of the energy storage battery and the power consumption of the converter can be accurately calculated through the simulation model, so as to obtain the simulation results of the energy management strategy.
- ⁇ t represents the difference between the request start time and the request end time of the current and voltage request.
- the auxiliary source power consumption is calculated by calling the auxiliary source model of the energy management system, so as to obtain the simulation result of the energy management strategy.
- simulation modeling method and terminal of the storage and charging station of the present invention are suitable for simulating the energy management strategy, and can calculate the economic cost index of the power station operation under different configurations and energy management strategies through simulation, and the following will be implemented in detail Way to explain:
- the initial value of the energy management strategy parameters in the simulation modeling including but not limited to the current output power of the PCS (energy storage converter), the SOC of the energy storage battery (State of Charge, state of charge), energy storage battery FCC (Full Charge Capacity (full charge capacity), DCDC (DC converter) current output voltage and current, etc.;
- a simulation record set S is established according to requirements, and the record set S contains the voltage and current requests of vehicles corresponding to charging piles 1 ⁇ n within m time periods, as well as the corresponding request time. If a charging pile is not charging, the request is 0.
- the records are extracted in chronological order and simulated.
- the energy storage battery model F ess is called to update the state of charge SOC i of the energy storage battery and the DC bus voltage V i of the storage and charging station:
- V i , SOC i F ess (SOC i-1 , V i-1 , W e );
- W e represents the output amount of the energy storage battery, and i represents the time period
- W pa , P pa F PCS (W p , ⁇ t);
- Wp represents the power output of the converter
- ⁇ t represents the difference between the request start time and the request end time of the current and voltage request.
- ⁇ t represents the difference between the request start time and the request end time of the current and voltage request.
- auxiliary source model F ap of the energy management system in addition to calling the auxiliary source model F ap of the energy management system to calculate the auxiliary source power consumption W ap , it is also necessary to call other models to calculate the power consumption of other electrical appliances.
- a simulation modeling terminal of a storage and charging station including a memory, a processor, and a computer program stored on the memory and operable on the processor, and the processor implements the computer program when executing the computer program
- a simulation modeling terminal of a storage and charging station including a memory, a processor, and a computer program stored on the memory and operable on the processor, and the processor implements the computer program when executing the computer program
- the present invention provides a simulation modeling method and terminal for a storage and charging station.
- the parameters of the energy storage battery and the converter are calculated according to the parameter values of the energy management strategy.
- Output quota which needs to be able to calculate the total power demand of multiple charging piles by obtaining the voltage and current requests received by multiple charging piles within a preset period of time, so that the output quota of energy storage batteries and converters is equal to the total power demand, So as to calculate the output amount more accurately; calculate the state of charge of the energy storage battery and the power consumption of the converter according to the output amount; judge the output amount of the converter and the energy storage battery, the state of charge of the energy storage battery and the inverter Whether the power consumption of the current converter meets the constraints of the energy management strategy, if it is met and there is no device alarm during the execution of the energy management strategy, record the simulation results corresponding to the energy management strategy, if not, generate a simulation record and count the simulation As a result
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- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Power Engineering (AREA)
- Computer Hardware Design (AREA)
- Evolutionary Computation (AREA)
- Geometry (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Charge And Discharge Circuits For Batteries Or The Like (AREA)
- Supply And Distribution Of Alternating Current (AREA)
Abstract
本发明公开了一种储充站仿真建模方法及终端，设置能量管理策略的参数值和约束条件后，根据能量管理策略的参数值，计算储能电池和变流器的出力额度，根据计算结果计算储能电池的荷电状态和变流器的耗电情况；判断变流器和储能电池的出力额度、储能电池的荷电状态以及变流器的耗电情况是否均符合能量管理策略的约束条件，若符合且执行能量管理策略期间不存在设备告警，则记录能量管理策略对应的仿真结果；因此，对设置好的能量管理策略进行仿真计算，并根据仿真数据判断能量管理策略是否符合执行条件，从而自动预测能量管理策略的运行结果。
Description
本发明涉及新能源技术领域，特别涉及一种储充站仿真建模方法及终端。
由于传统能源的不断减少以及传统能源对环境的污染，新能源的利用和开发被提到了新的高度。储能充电站中含有一组储能电池，可以在充电站有空闲的时候将一部分电能事先存储于储能电池中，留作之后电动汽车有用电需求的时候再放出，从而提高了充电站一段时间内的输出功率，并且通过削峰填谷的方式降低充电站的电费。
但是，因电动汽车充放电需求的不确定性、充电站业务量的变化、电费方案的变化、储能电池充放电的折旧成本、电站各用电器在不同工况下的能量转化效率以及运营安全等问题，不同设备在使用过程中的性能有可能发生变化，较难预测能量管理策略的运行结果。
本发明所要解决的技术问题是：提供了一种储充站仿真建模方法及终端，能够预测能量管理策略的运行结果。
为了解决上述技术问题，本发明采用的技术方案为：
一种储充站仿真建模方法，包括步骤：
设置能量管理策略的参数值和约束条件；
根据所述能量管理策略的参数值，计算变流器和储能电池的出力额度；
基于所述储能电池和变流器的出力额度，分别计算储能电池的荷电状态和所述变流器的耗电情况；
判断所述变流器和储能电池的出力额度、所述储能电池的荷电状态和所述变流器的耗电情况是否均符合所述能量管理策略的约束条件，若是，则判断仿真期间是否存在设备告警，若不存在告警，则记录所述能量管理策略对应的仿真结果。
为了解决上述技术问题，本发明采用的另一种技术方案为：
一种储充站仿真建模终端，包括存储器、处理器以及存储在所述存储器上并可在处理器上运行的计算机程序，所述处理器执行所述计算机程序时实现以下步骤：
设置能量管理策略的参数值和约束条件；
根据所述能量管理策略的参数值，计算变流器和储能电池的出力额度；
基于所述储能电池和变流器的出力额度，分别计算储能电池的荷电状态和所述变流器的耗电情况；
判断所述变流器和储能电池的出力额度、所述储能电池的荷电状态和所述变流器的耗电情况是否均符合所述能量管理策略的约束条件，若是，则判断仿真期间是否存在设备告警，若不存在告警，则记录所述能量管理策略对应的仿真结果。
本发明的有益效果在于：设置能量管理策略的参数值和约束条件后，根据能量管理策略的参数值，计算储能电池和变流器的出力额度，根据计算结果计算储能电池的荷电状态和变流器的耗电情况；判断变流器和储能电池的出力额度、储能电池的荷电状态以及变流器的耗电情况是否均符合能量管理策略的约束条件，若符合且执行能量管理策略期间不存在设备告警，则记录能量管理策略对应的仿真结果；因此，对设置好的能量管理策略进行仿真计算，并根据仿真数据判断能量管理策略是否符合执行条件，从而自动预测能量管理策略的运行结果。
图1为本发明实施例的一种储充站仿真建模方法的流程图；
图2为本发明实施例的一种储充站仿真建模终端的示意图；
图3为本发明实施例的一种储充站仿真建模方法的具体步骤流程图。
为详细说明本发明的技术内容、所实现目的及效果，以下结合实施方式并配合附图予以说明。
请参照图1和图3，本发明实施例提供了一种储充站仿真建模方法，包括步骤：
设置能量管理策略的参数值和约束条件；
根据所述能量管理策略的参数值，计算变流器和储能电池的出力额度；
基于所述储能电池和变流器的出力额度，分别计算储能电池的荷电状态和所述变流器的耗电情况；
判断所述变流器和储能电池的出力额度、所述储能电池的荷电状态和所述变流器的耗电情况是否均符合所述能量管理策略的约束条件，若是，则判断仿真期间是否存在设备告警，若不存在告警，则记录所述能量管理策略对应的仿真结果。
从上述描述可知，本发明的有益效果在于：设置能量管理策略的参数值和约束条件后，根据能量管理策略的参数值，计算储能电池和变流器的出力额度，根据计算结果计算储能电池的荷电状态和变流器的耗电情况；判断变流器和储能电池的出力额度、储能电池的荷电状态以及变流器的耗电情况是否均符合能量管理策略的约束条件，若符合且执行能量管理策略期间不存在设备告警，则记录能量管理策略对应的仿真结果；因此，对设置好的能量管理策略进行仿真计算，并根据仿真数据判断能量管理策略是否符合执行条件，从而自动预测能量管理策略的运行结果。
进一步地，根据所述能量管理策略的参数值，计算变流器和储能电池的出力额度包括：
获取预设时段内多个充电桩分别接收的电压电流请求；
根据所述电压电流请求的请求信息，计算多个所述充电桩的总用电需求；
结合所述能量管理策略的参数值和所述总用电需求计算变流器和储能电池的出力额度。
由上述描述可知，通过获取预设时段内多个充电桩接收到电压电流请求，能够计算多个充电桩的总用电需求，从而能够结合能量管理策略的参数值和总用电需求计算变流器和储能电池的出力额度，因此结合充电桩的请求信息能够更最准确地计算出力额度。
进一步地，基于所述储能电池和变流器的出力额度，分别计算储能电池的荷电状态和所述变流器的耗电情况包括：
调用储能电池模型F
ess更新储能电池的荷电状态SOC
i和储充站的直流母线电压V
i：
V
i, SOC
i= F
ess(SOC
i-1,
V
i-1, W
e)；
式中，W
e表示所述储能电池的出力额度，i表示所述时段；
调用变流器模型F
PCS计算变流器的交流电的用电量W
pa和输出功率P
pa：
W
pa, P
pa = F
PCS(W
p,
Δt)；
式中，W
p表示所述变流器的出力额度，Δt表示所述电流电压请求的请求开始时间与请求结束时间的差值。
由上述描述可知，通过储能电池模型和储能电池的出力额度更新储能电池SOC和直流母线电压，通过变流器模型和变流器的出力额度计算交流电的用电量和输出功率，因此通过仿真模型能够准确计算出储能电池的荷电状态和变流器的耗电情况，以便于得到能量管理策略的仿真结果。
进一步地，基于所述储能电池和变流器的出力额度，分别计算储能电池的荷电状态和所述变流器的耗电情况之后包括：
调用能量管理***的辅源模型F
ap计算辅源功耗W
ap：
W
ap = F
ap(Δt)；
式中，Δt表示所述电流电压请求的请求开始时间与请求结束时间的差值。
由上述描述可知，通过调用能量管理***的辅源模型计算辅源功耗，以便于得到能量管理策略的仿真结果。
进一步地，判断所述变流器和储能电池的出力额度、所述储充站的功耗以及更新后所述储能电池的荷电状态是否均符合所述能量管理策略的约束条件，若否，则生成仿真记录并统计仿真结果。
由上述描述可知，当运行结果不符合能量管理策略的约束条件时，记录仿真过程中的数据并统计仿真结果，能够便于能量管理策略的修改与更新。
请参照图2，本发明另一实施例提供了一种储充站仿真建模终端，包括存储器、处理器以及存储在所述存储器上并可在处理器上运行的计算机程序，所述处理器执行所述计算机程序时实现以下步骤：
设置能量管理策略的参数值和约束条件；
根据所述能量管理策略的参数值，计算变流器和储能电池的出力额度；
基于所述储能电池和变流器的出力额度，分别计算储能电池的荷电状态和所述变流器的耗电情况；
判断所述变流器和储能电池的出力额度、所述储能电池的荷电状态和所述变流器的耗电情况是否均符合所述能量管理策略的约束条件，若是，则判断仿真期间是否存在设备告警，若不存在告警，则记录所述能量管理策略对应的仿真结果。
由上述描述可知，本发明的有益效果在于：设置能量管理策略的参数值和约束条件后，根据能量管理策略的参数值，计算储能电池和变流器的出力额度，根据计算结果计算储能电池的荷电状态和变流器的耗电情况；判断变流器和储能电池的出力额度、储能电池的荷电状态以及变流器的耗电情况是否均符合能量管理策略的约束条件，若符合且执行能量管理策略期间不存在设备告警，则记录能量管理策略对应的仿真结果；因此，对设置好的能量管理策略进行仿真计算，并根据仿真数据判断能量管理策略是否符合执行条件，从而自动预测能量管理策略的运行结果。
进一步地，根据所述能量管理策略的参数值，计算变流器和储能电池的出力额度包括：
获取预设时段内多个充电桩分别接收的电压电流请求；
根据所述电压电流请求的请求信息，计算多个所述充电桩的总用电需求；
结合所述能量管理策略的参数值和所述总用电需求计算变流器和储能电池的出力额度。
由上述描述可知，通过获取预设时段内多个充电桩接收到电压电流请求，能够计算多个充电桩的总用电需求，从而能够结合能量管理策略的参数值和总用电需求计算变流器和储能电池的出力额度，因此结合充电桩的请求信息能够更最准确地计算出力额度。
进一步地，基于所述储能电池和变流器的出力额度，分别计算储能电池的荷电状态和所述变流器的耗电情况包括：
调用储能电池模型F
ess更新储能电池的荷电状态SOC
i和储充站的直流母线电压V
i：
V
i, SOC
i = F
ess(SOC
i-1,
V
i-1, W
e)；
式中，W
e表示所述储能电池的出力额度，i表示所述时段；
调用变流器模型F
PCS计算变流器的交流电的用电量W
pa和输出功率P
pa：
W
pa, P
pa = F
PCS(W
p,
Δt)；
式中，W
p表示所述变流器的出力额度，Δt表示所述电流电压请求的请求开始时间与请求结束时间的差值。
由上述描述可知，通过储能电池模型和储能电池的出力额度更新储能电池SOC和直流母线电压，通过变流器模型和变流器的出力额度计算交流电的用电量和输出功率，因此通过仿真模型能够准确计算出储能电池的荷电状态和变流器的耗电情况，以便于得到能量管理策略的仿真结果。
进一步地，基于所述储能电池和变流器的出力额度，分别计算储能电池的荷电状态和所述变流器的耗电情况之后包括：
调用能量管理***的辅源模型F
ap计算辅源功耗W
ap：
W
ap = F
ap(Δt)；
式中，Δt表示所述电流电压请求的请求开始时间与请求结束时间的差值。
由上述描述可知，通过调用能量管理***的辅源模型计算辅源功耗，以便于得到能量管理策略的仿真结果。
进一步地，判断所述变流器和储能电池的出力额度、所述储充站的功耗以及更新后所述储能电池的荷电状态是否均符合所述能量管理策略的约束条件，若否，则生成仿真记录并统计仿真结果。
由上述描述可知，当运行结果不符合能量管理策略的约束条件时，记录仿真过程中的数据并统计仿真结果，能够便于能量管理策略的修改与更新。
本发明上述一种储充站仿真建模方法及终端，适用于对能量管理策略进行仿真，可以通过仿真的方式计算出不同的配置和能量管理策略下电站运营的经济成本指标，以下通过具体实施方式进行说明：
实施例一
请参照图1和图3，一种储充站仿真建模方法，包括步骤：
S1、设置能量管理策略的参数值和约束条件。
具体的，设定仿真建模中能量管理策略参数的初始值，包括但不限于PCS（储能变流器）当前输出功率、储能电池SOC（State
of Charge，荷电状态）、储能电池FCC（Full
Charge Capacity 充满电容量）、DCDC（直流变换器）当前输出电压电流等；
设定仿真建模中能量管理策略的约束条件，包括但不限于PCS最大功率、储能电池容量、储能电池最大电压电流输出能力、DCDC最大电压电流输出能力等。
S2、根据所述能量管理策略的参数值，计算变流器和储能电池的出力额度。
其中，获取预设时段内多个充电桩分别接收的电压电流请求；
根据所述电压电流请求的请求信息，计算多个所述充电桩的总用电需求；
结合所述能量管理策略的参数值和所述总用电需求计算变流器和储能电池的出力额度。
具体的，在本实施例中，根据需求建立仿真记录集S，记录集S中包含充电桩1~n对应的车辆在m个时段内的电压电流请求，以及对应的请求时间，如果某一时刻某台充电桩没有充电，则请求为0。
设定时长阈值W，对于记录集S中，任意两条时间相邻的记录的时间差绝对值t，需满足：max(t) <= W，否则记录集视为无效；
对于有效记录集，按照时间先后顺序提取记录并进行仿真。
从仿真数据库中获取一条最新的未处理的电动汽车充电请求数据，包含：请求的开始时间T
si、请求的结束时间T
ei、充电桩1~n对应的车辆1~n请求的电压V
i1~V
in、充电桩1~n对应的车辆1~n请求的电流I
i1~I
in；
计算n个充电桩在时段i的充电桩用电需求W
i1 ~ W
in，W
ij = V
ij
* I
ij *Δt
i，其中Δt = T
ei-T
si；
计算n个充电桩的直流母线用电需求WD
i1 ~
WD
in，计算方法为：WD
ij = W
ij / F
DCj(V
ij, I
ij)，其中F
DCj为充电桩j对应的DCDC的转化率模型；
根据WD
i1
~ WD
in计算母线总用电需求WDS；
根据仿真策略计算PCS出力额度W
p和储能电池出力额度W
e，符合约束条件：W
ds = W
p
+ W
e。
S3、基于所述储能电池和变流器的出力额度，分别计算储能电池的荷电状态和所述变流器的耗电情况。
其中，调用储能电池模型F
ess更新储能电池的荷电状态SOC
i和储充站的直流母线电压V
i：
V
i, SOC
i = F
ess(SOC
i-1,
V
i-1, W
e)；
式中，W
e表示所述储能电池的出力额度，i表示所述时段；
调用变流器模型F
PCS计算变流器的交流电的用电量W
pa和输出功率P
pa：
W
pa, P
pa = F
PCS(W
p,
Δt)；
式中，W
p表示所述变流器的出力额度，Δt表示所述电流电压请求的请求开始时间与请求结束时间的差值。
其中，基于所述储能电池和变流器的出力额度，分别计算储能电池的荷电状态和所述变流器的耗电情况之后包括：
调用能量管理***的辅源模型F
ap计算辅源功耗W
ap：
W
ap = F
ap(Δt)；
式中，Δt表示所述电流电压请求的请求开始时间与请求结束时间的差值。
具体的，除了调用能量管理***的辅源模型F
ap计算辅源功耗W
ap，还需要调用其他模型计算其他用电器的功耗。
S4、判断所述变流器和储能电池的出力额度、所述储能电池的荷电状态和所述变流器的耗电情况是否均符合所述能量管理策略的约束条件，若是，则判断仿真期间是否存在设备告警，若不存在告警，则记录所述能量管理策略对应的仿真结果。
具体的，判断所述变流器和储能电池的出力额度、储能电池的荷电状态、变流器的耗电情况、辅源功耗和其他用电器的功耗是否均符合所述能量管理策略的约束条件，若符合，则判断仿真期间是否存在设备告警，若不存在告警，则记录仿真结果，若存在告警，则记录告警事件并记录仿真结果，其中记录的仿真结果为AC总功耗、各部品功耗以及其他仿真数据；若不符合，则生成仿真记录并统计仿真结果。
实施例二
请参照图2，一种储充站仿真建模终端，包括存储器、处理器以及存储在所述存储器上并可在处理器上运行的计算机程序，所述处理器执行所述计算机程序时实现实施例一的储充站仿真建模方法的各个步骤。
综上所述，本发明提供的一种储充站仿真建模方法及终端，设置能量管理策略的参数值和约束条件后，根据能量管理策略的参数值，计算储能电池和变流器的出力额度，其中需要通过获取预设时段内多个充电桩接收到电压电流请求，能够计算多个充电桩的总用电需求，使储能电池和变流器的出力额度等于总用电需求，从而更最准确地计算出力额度；根据出力额度计算储能电池的荷电状态和变流器的耗电情况；判断变流器和储能电池的出力额度、储能电池的荷电状态以及变流器的耗电情况是否均符合能量管理策略的约束条件，若符合且执行能量管理策略期间不存在设备告警，则记录能量管理策略对应的仿真结果，若不符合，则生成仿真记录并统计仿真结果，便于后续能量管理策略的修改与更新；因此，对设置好的能量管理策略进行仿真计算，并根据仿真数据判断能量管理策略是否符合执行条件，从而自动预测能量管理策略的运行结果。
以上所述仅为本发明的实施例，并非因此限制本发明的专利范围，凡是利用本发明说明书及附图内容所作的等同变换，或直接或间接运用在相关的技术领域，均同理包括在本发明的专利保护范围内。
Claims (10)
- 一种储充站仿真建模方法，其特征在于，包括步骤：设置能量管理策略的参数值和约束条件；根据所述能量管理策略的参数值，计算变流器和储能电池的出力额度；基于所述储能电池和变流器的出力额度，分别计算储能电池的荷电状态和所述变流器的耗电情况；判断所述变流器和储能电池的出力额度、所述储能电池的荷电状态和所述变流器的耗电情况是否均符合所述能量管理策略的约束条件，若是，则判断仿真期间是否存在设备告警，若不存在告警，则记录所述能量管理策略对应的仿真结果。
- 根据权利要求1所述的一种储充站仿真建模方法，其特征在于，根据所述能量管理策略的参数值，计算变流器和储能电池的出力额度包括：获取预设时段内多个充电桩分别接收的电压电流请求；根据所述电压电流请求的请求信息，计算多个所述充电桩的总用电需求；结合所述能量管理策略的参数值和所述总用电需求计算变流器和储能电池的出力额度。
- 根据权利要求2所述的一种储充站仿真建模方法，其特征在于，基于所述储能电池和变流器的出力额度，分别计算储能电池的荷电状态和所述变流器的耗电情况包括：调用储能电池模型F ess更新储能电池的荷电状态SOC i和储充站的直流母线电压V i：V i, SOC i = F ess(SOC i-1, V i-1, W e)；式中，W e表示所述储能电池的出力额度，i表示所述时段；调用变流器模型F PCS计算变流器的交流电的用电量W pa和输出功率P pa：W pa, P pa = F PCS(W p, Δt)；式中，W p表示所述变流器的出力额度，Δt表示所述电流电压请求的请求开始时间与请求结束时间的差值。
- 根据权利要求2所述的一种储充站仿真建模方法，其特征在于，基于所述储能电池和变流器的出力额度，分别计算储能电池的荷电状态和所述变流器的耗电情况之后包括：调用能量管理***的辅源模型F ap计算辅源功耗W ap：W ap = F ap(Δt)；式中，Δt表示所述电流电压请求的请求开始时间与请求结束时间的差值。
- 根据权利要求1所述的一种储充站仿真建模方法，其特征在于，判断所述变流器和储能电池的出力额度、所述储充站的功耗以及更新后所述储能电池的荷电状态是否均符合所述能量管理策略的约束条件，若否，则生成仿真记录并统计仿真结果。
- 一种储充站仿真建模终端，包括存储器、处理器以及存储在所述存储器上并可在处理器上运行的计算机程序，其特征在于，所述处理器执行所述计算机程序时实现以下步骤：设置能量管理策略的参数值和约束条件；根据所述能量管理策略的参数值，计算变流器和储能电池的出力额度；基于所述储能电池和变流器的出力额度，分别计算储能电池的荷电状态和所述变流器的耗电情况；判断所述变流器和储能电池的出力额度、所述储能电池的荷电状态和所述变流器的耗电情况是否均符合所述能量管理策略的约束条件，若是，则判断仿真期间是否存在设备告警，若不存在告警，则记录所述能量管理策略对应的仿真结果。
- 根据权利要求6所述的一种储充站仿真建模终端，其特征在于，根据所述能量管理策略的参数值，计算变流器和储能电池的出力额度包括：获取预设时段内多个充电桩分别接收的电压电流请求；根据所述电压电流请求的请求信息，计算多个所述充电桩的总用电需求；结合所述能量管理策略的参数值和所述总用电需求计算变流器和储能电池的出力额度。
- 根据权利要求7所述的一种储充站仿真建模终端，其特征在于，基于所述储能电池和变流器的出力额度，分别计算储能电池的荷电状态和所述变流器的耗电情况包括：调用储能电池模型F ess更新储能电池的荷电状态SOC i和储充站的直流母线电压V i：V i, SOC i = F ess(SOC i-1, V i-1, W e)；式中，W e表示所述储能电池的出力额度，i表示所述时段；调用变流器模型F PCS计算变流器的交流电的用电量W pa和输出功率P pa：W pa, P pa = F PCS(W p, Δt)；式中，W p表示所述变流器的出力额度，Δt表示所述电流电压请求的请求开始时间与请求结束时间的差值。
- 根据权利要求7所述的一种储充站仿真建模终端，其特征在于，基于所述储能电池和变流器的出力额度，分别计算储能电池的荷电状态和所述变流器的耗电情况之后包括：调用能量管理***的辅源模型F ap计算辅源功耗W ap：W ap = F ap(Δt)；式中，Δt表示所述电流电压请求的请求开始时间与请求结束时间的差值。
- 根据权利要求6所述的一种储充站仿真建模终端，其特征在于，判断所述变流器和储能电池的出力额度、所述储充站的功耗以及更新后所述储能电池的荷电状态是否均符合所述能量管理策略的约束条件，若否，则生成仿真记录并统计仿真结果。
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